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EUROPAR
2007
Springer

Locality Optimized Shared-Memory Implementations of Iterated Runge-Kutta Methods

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Locality Optimized Shared-Memory Implementations of Iterated Runge-Kutta Methods
Iterated Runge-Kutta (IRK) methods are a class of explicit solution methods for initial value problems of ordinary differential equations (ODEs) which possess a considerable potential for parallelism across the method and the ODE system. In this paper, we consider the sequential and parallel implementation of IRK methods with the main focus on the optimization of the locality behavior. We introduce different implementation variants for sequential and shared-memory computer systems and analyze their runtime and cache performance on two modern supercomputer systems.
Matthias Korch, Thomas Rauber
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where EUROPAR
Authors Matthias Korch, Thomas Rauber
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